diff options
Diffstat (limited to 'modules/api')
| -rw-r--r-- | modules/api/api.py | 45 | ||||
| -rw-r--r-- | modules/api/models.py | 28 |
2 files changed, 52 insertions, 21 deletions
diff --git a/modules/api/api.py b/modules/api/api.py index 5a9ac5f1..376f7f04 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -150,6 +150,7 @@ class Api: self.add_api_route("/sdapi/v1/train/embedding", self.train_embedding, methods=["POST"], response_model=TrainResponse) self.add_api_route("/sdapi/v1/train/hypernetwork", self.train_hypernetwork, methods=["POST"], response_model=TrainResponse) self.add_api_route("/sdapi/v1/memory", self.get_memory, methods=["GET"], response_model=MemoryResponse) + self.add_api_route("/sdapi/v1/scripts", self.get_scripts_list, methods=["GET"], response_model=ScriptsList) def add_api_route(self, path: str, endpoint, **kwargs): if shared.cmd_opts.api_auth: @@ -174,36 +175,44 @@ class Api: script_idx = script_name_to_index(script_name, script_runner.selectable_scripts) script = script_runner.selectable_scripts[script_idx] return script, script_idx + + def get_scripts_list(self): + t2ilist = [str(title.lower()) for title in scripts.scripts_txt2img.titles] + i2ilist = [str(title.lower()) for title in scripts.scripts_img2img.titles] + + return ScriptsList(txt2img = t2ilist, img2img = i2ilist) def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI): script, script_idx = self.get_script(txt2imgreq.script_name, scripts.scripts_txt2img) - populate = txt2imgreq.copy(update={ # Override __init__ params + populate = txt2imgreq.copy(update={ # Override __init__ params "sampler_name": validate_sampler_name(txt2imgreq.sampler_name or txt2imgreq.sampler_index), - "do_not_save_samples": True, - "do_not_save_grid": True - } - ) + "do_not_save_samples": not txt2imgreq.save_images, + "do_not_save_grid": not txt2imgreq.save_images, + }) if populate.sampler_name: populate.sampler_index = None # prevent a warning later on args = vars(populate) args.pop('script_name', None) + send_images = args.pop('send_images', True) + args.pop('save_images', None) + with self.queue_lock: p = StableDiffusionProcessingTxt2Img(sd_model=shared.sd_model, **args) + p.outpath_grids = opts.outdir_txt2img_grids + p.outpath_samples = opts.outdir_txt2img_samples shared.state.begin() if script is not None: - p.outpath_grids = opts.outdir_txt2img_grids - p.outpath_samples = opts.outdir_txt2img_samples p.script_args = [script_idx + 1] + [None] * (script.args_from - 1) + p.script_args processed = scripts.scripts_txt2img.run(p, *p.script_args) else: processed = process_images(p) shared.state.end() - b64images = list(map(encode_pil_to_base64, processed.images)) + b64images = list(map(encode_pil_to_base64, processed.images)) if send_images else [] return TextToImageResponse(images=b64images, parameters=vars(txt2imgreq), info=processed.js()) @@ -218,13 +227,12 @@ class Api: if mask: mask = decode_base64_to_image(mask) - populate = img2imgreq.copy(update={ # Override __init__ params + populate = img2imgreq.copy(update={ # Override __init__ params "sampler_name": validate_sampler_name(img2imgreq.sampler_name or img2imgreq.sampler_index), - "do_not_save_samples": True, - "do_not_save_grid": True, - "mask": mask - } - ) + "do_not_save_samples": not img2imgreq.save_images, + "do_not_save_grid": not img2imgreq.save_images, + "mask": mask, + }) if populate.sampler_name: populate.sampler_index = None # prevent a warning later on @@ -232,21 +240,24 @@ class Api: args.pop('include_init_images', None) # this is meant to be done by "exclude": True in model, but it's for a reason that I cannot determine. args.pop('script_name', None) + send_images = args.pop('send_images', True) + args.pop('save_images', None) + with self.queue_lock: p = StableDiffusionProcessingImg2Img(sd_model=shared.sd_model, **args) p.init_images = [decode_base64_to_image(x) for x in init_images] + p.outpath_grids = opts.outdir_img2img_grids + p.outpath_samples = opts.outdir_img2img_samples shared.state.begin() if script is not None: - p.outpath_grids = opts.outdir_img2img_grids - p.outpath_samples = opts.outdir_img2img_samples p.script_args = [script_idx + 1] + [None] * (script.args_from - 1) + p.script_args processed = scripts.scripts_img2img.run(p, *p.script_args) else: processed = process_images(p) shared.state.end() - b64images = list(map(encode_pil_to_base64, processed.images)) + b64images = list(map(encode_pil_to_base64, processed.images)) if send_images else [] if not img2imgreq.include_init_images: img2imgreq.init_images = None diff --git a/modules/api/models.py b/modules/api/models.py index cba43d3b..fa1c40df 100644 --- a/modules/api/models.py +++ b/modules/api/models.py @@ -14,8 +14,8 @@ API_NOT_ALLOWED = [ "outpath_samples", "outpath_grids", "sampler_index", - "do_not_save_samples", - "do_not_save_grid", + # "do_not_save_samples", + # "do_not_save_grid", "extra_generation_params", "overlay_images", "do_not_reload_embeddings", @@ -100,13 +100,29 @@ class PydanticModelGenerator: StableDiffusionTxt2ImgProcessingAPI = PydanticModelGenerator( "StableDiffusionProcessingTxt2Img", StableDiffusionProcessingTxt2Img, - [{"key": "sampler_index", "type": str, "default": "Euler"}, {"key": "script_name", "type": str, "default": None}, {"key": "script_args", "type": list, "default": []}] + [ + {"key": "sampler_index", "type": str, "default": "Euler"}, + {"key": "script_name", "type": str, "default": None}, + {"key": "script_args", "type": list, "default": []}, + {"key": "send_images", "type": bool, "default": True}, + {"key": "save_images", "type": bool, "default": False}, + ] ).generate_model() StableDiffusionImg2ImgProcessingAPI = PydanticModelGenerator( "StableDiffusionProcessingImg2Img", StableDiffusionProcessingImg2Img, - [{"key": "sampler_index", "type": str, "default": "Euler"}, {"key": "init_images", "type": list, "default": None}, {"key": "denoising_strength", "type": float, "default": 0.75}, {"key": "mask", "type": str, "default": None}, {"key": "include_init_images", "type": bool, "default": False, "exclude" : True}, {"key": "script_name", "type": str, "default": None}, {"key": "script_args", "type": list, "default": []}] + [ + {"key": "sampler_index", "type": str, "default": "Euler"}, + {"key": "init_images", "type": list, "default": None}, + {"key": "denoising_strength", "type": float, "default": 0.75}, + {"key": "mask", "type": str, "default": None}, + {"key": "include_init_images", "type": bool, "default": False, "exclude" : True}, + {"key": "script_name", "type": str, "default": None}, + {"key": "script_args", "type": list, "default": []}, + {"key": "send_images", "type": bool, "default": True}, + {"key": "save_images", "type": bool, "default": False}, + ] ).generate_model() class TextToImageResponse(BaseModel): @@ -267,3 +283,7 @@ class EmbeddingsResponse(BaseModel): class MemoryResponse(BaseModel): ram: dict = Field(title="RAM", description="System memory stats") cuda: dict = Field(title="CUDA", description="nVidia CUDA memory stats") + +class ScriptsList(BaseModel): + txt2img: list = Field(default=None,title="Txt2img", description="Titles of scripts (txt2img)") + img2img: list = Field(default=None,title="Img2img", description="Titles of scripts (img2img)")
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